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The paper presents the overview of the ImageCLEF 2022 Aware task whose final objective is to make users more aware about the consequences of posting information on social networks. This is important insofar as users are often unaware about the effects of personal data sharing. Focus is put on modeling the impact of sharing impactful real-life situations such as searching for a bank loan, an accommodation, or a job. Since photos are one of the main types of data shared online, the task is instantiated as a photographic user profile assessment. Participants receive a training and validation dataset which includes a set of photographic profiles which are manually rated for each situation. They are required to train algorithms which rate and then rank test profiles in each tested situation. The correlation between automatic and manual profile rankings is used to measure the performance of algorithms. The overview discusses the task settings, the dataset constitution process, and the approaches proposed this year.